Data
AirlinesCodrnaAdult

AirlinesCodrnaAdult

active ARFF Publicly available Visibility: public Uploaded 14-02-2015 by Jan van Rijn
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30 features

Delay (target)nominal2 unique values
0 missing
Airlinenominal18 unique values
0 missing
Flightnumeric6585 unique values
0 missing
AirportFromnominal293 unique values
0 missing
AirportTonominal293 unique values
0 missing
DayOfWeeknominal7 unique values
0 missing
Timenumeric1131 unique values
0 missing
Lengthnumeric426 unique values
0 missing
codrna_X1numeric1327 unique values
0 missing
codrna_X2numeric43 unique values
0 missing
codrna_X3numeric228 unique values
0 missing
codrna_X4numeric228 unique values
0 missing
codrna_X5numeric220 unique values
0 missing
codrna_X6numeric228 unique values
0 missing
codrna_X7numeric228 unique values
0 missing
codrna_X8numeric220 unique values
0 missing
agenominal5 unique values
0 missing
workclassnominal8 unique values
3129 missing
fnlwgtnumeric28523 unique values
0 missing
educationnominal16 unique values
0 missing
education-numnumeric16 unique values
0 missing
marital-statusnominal7 unique values
0 missing
occupationnominal14 unique values
3139 missing
relationshipnominal6 unique values
0 missing
racenominal5 unique values
0 missing
sexnominal2 unique values
0 missing
capitalgainnominal5 unique values
0 missing
capitallossnominal5 unique values
0 missing
hoursperweeknominal5 unique values
0 missing
native-countrynominal41 unique values
1007 missing

107 properties

1076790
Number of instances (rows) of the dataset.
30
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
7275
Number of missing values in the dataset.
4085
Number of instances with at least one value missing.
13
Number of numeric attributes.
17
Number of nominal attributes.
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
83637.47
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0.58
Second quartile (Median) of skewness among attributes of the numeric type.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
0.06
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
6.67
Percentage of binary attributes.
0.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.23
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
65.47
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
293
The maximum number of distinct values among attributes of the nominal type.
-6.3
Minimum skewness among attributes of the numeric type.
0.38
Percentage of instances having missing values.
1.66
Third quartile of entropy among attributes.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
7.74
Maximum skewness among attributes of the numeric type.
0.08
Minimum standard deviation of attributes of the numeric type.
0.02
Percentage of missing values.
9.36
Third quartile of kurtosis among attributes of the numeric type.
0.57
Average class difference between consecutive instances.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
35324.01
Maximum standard deviation of attributes of the numeric type.
43.99
Percentage of instances belonging to the least frequent class.
43.33
Percentage of numeric attributes.
669.97
Third quartile of means among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.23
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.02
Average entropy of the attributes.
473652
Number of instances belonging to the least frequent class.
56.67
Percentage of nominal attributes.
0.02
Third quartile of mutual information between the nominal attributes and the target attribute.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
13.13
Mean kurtosis among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.15
First quartile of entropy among attributes.
2.12
Third quartile of skewness among attributes of the numeric type.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
6637.78
Mean of means among attributes of the numeric type.
0.38
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.4
First quartile of kurtosis among attributes of the numeric type.
238.39
Third quartile of standard deviation of attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.23
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.02
Average mutual information between the nominal attributes and the target attribute.
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.32
First quartile of means among attributes of the numeric type.
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.35
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
66.61
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
94.53
Standard deviation of the number of distinct values among attributes of the nominal type.
0.2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
43.06
Average number of distinct values among the attributes of the nominal type.
-0.71
First quartile of skewness among attributes of the numeric type.
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.35
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.74
Mean skewness among attributes of the numeric type.
0.11
First quartile of standard deviation of attributes of the numeric type.
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.24
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
56.01
Percentage of instances belonging to the most frequent class.
2897.39
Mean standard deviation of attributes of the numeric type.
0.33
Second quartile (Median) of entropy among attributes.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.99
Entropy of the target attribute values.
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
603138
Number of instances belonging to the most frequent class.
0.03
Minimal entropy among attributes.
4.68
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
4.27
Maximum entropy among attributes.
-1.66
Minimum kurtosis among attributes of the numeric type.
0.62
Second quartile (Median) of means among attributes of the numeric type.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.35
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
86.97
Maximum kurtosis among attributes of the numeric type.
0.22
Minimum of means among attributes of the numeric type.
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

13 tasks

0 runs - estimation_procedure: 33% Holdout set - target_feature: Delay
253 runs - estimation_procedure: Interleaved Test then Train - target_feature: Delay
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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